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<body class="w3-container">
<div class="w3-container w3-orange">
  <h1>DataFrame</h1>
</div>
<div class="w3-container">
  <h2>Attributes and underlying data</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="20%">
    <col width="80%">
    </colgroup>
    <tr>
      <th>属性</th>
      <th>描述</th>
    </tr>
    <tr>
      <td>DataFrame.columns</td>
      <td>The column labels of the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.index</td>
      <td>The index (row labels) of the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.dtypes</td>
      <td>Return the dtypes in the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.ftypes</td>
      <td>Return the ftypes (indication of sparse/dense and dtype) in DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.get_dtype_counts()</td>
      <td>Return counts of unique dtypes in this object. </td>
    </tr>
    <tr>
      <td>DataFrame.get_ftype_counts()</td>
      <td>(DEPRECATED) Return counts of unique ftypes in this object. </td>
    </tr>
    <tr>
      <td>DataFrame.select_dtypes([include, exclude])</td>
      <td>Return a subset of the DataFrame’s columns based on the column dtypes.</td>
    </tr>
    <tr>
      <td>DataFrame.values</td>
      <td> Return a Numpy representation of the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.get_values()</td>
      <td>Return an ndarray after converting sparse values to dense. </td>
    </tr>
    <tr>
      <td>DataFrame.axes</td>
      <td>Return a list representing the axes of the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.ndim</td>
      <td>Return an int representing the number of axes / array dimensions.</td>
    </tr>
    <tr>
      <td>DataFrame.size</td>
      <td>Return an int representing the number of elements in this object.</td>
    </tr>
    <tr>
      <td>DataFrame.shape</td>
      <td>Return a tuple representing the dimensionality of the DataFrame.</td>
    </tr>
    <tr>
      <td>DataFrame.memory_usage([index, deep])</td>
      <td>Return the memory usage of each column in bytes.</td>
    </tr>
    <tr>
      <td>DataFrame.empty</td>
      <td>Indicator whether DataFrame is empty.</td>
    </tr>
    <tr>
      <td>DataFrame.is_copy</td>
      <td>Return the copy.</td>
    </tr>
  </table>
</div>
<br>
<div class="w3-container">
  <h2>Conversion</h2>
  <table class="w3-table-all w3-hoverable">
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    <col width="20%">
    <col width="80%">
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.astype.html#pandas.DataFrame.astype" title="pandas.DataFrame.astype">DataFrame.astype</a>(dtype[, copy, errors])</td>
        <td>Cast a pandas object to a specified dtype dtype.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.convert_objects.html#pandas.DataFrame.convert_objects" title="pandas.DataFrame.convert_objects">DataFrame.convert_objects</a>([convert_dates, …])</td>
        <td>(DEPRECATED) Attempt to infer better dtype for object columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.infer_objects.html#pandas.DataFrame.infer_objects" title="pandas.DataFrame.infer_objects">DataFrame.infer_objects</a>()</td>
        <td>Attempt to infer better dtypes for object columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.copy.html#pandas.DataFrame.copy" title="pandas.DataFrame.copy">DataFrame.copy</a>([deep])</td>
        <td>Make a copy of this object&rsquo;s indices and data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.isna.html#pandas.DataFrame.isna" title="pandas.DataFrame.isna">DataFrame.isna</a>()</td>
        <td>Detect missing values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.notna.html#pandas.DataFrame.notna" title="pandas.DataFrame.notna">DataFrame.notna</a>()</td>
        <td>Detect existing (non-missing) values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.bool.html#pandas.DataFrame.bool" title="pandas.DataFrame.bool">DataFrame.bool</a>()</td>
        <td>Return the bool of a single element PandasObject.</td>
      </tr>
    </tbody>
  </table>
</div>

<div class="w3-container">
  <h2>Binary operator functions</h2>
  <table class="w3-table-all w3-hoverable">
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    <col width="90%">
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.add.html#pandas.DataFrame.add" title="pandas.DataFrame.add">DataFrame.add</a>(other[, axis, level, fill_value])</td>
        <td>Addition of dataframe and other, element-wise (binary operator add).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sub.html#pandas.DataFrame.sub" title="pandas.DataFrame.sub">DataFrame.sub</a>(other[, axis, level, fill_value])</td>
        <td>Subtraction of dataframe and other, element-wise (binary operator sub).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.mul.html#pandas.DataFrame.mul" title="pandas.DataFrame.mul">DataFrame.mul</a>(other[, axis, level, fill_value])</td>
        <td>Multiplication of dataframe and other, element-wise (binary operator mul).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.div.html#pandas.DataFrame.div" title="pandas.DataFrame.div">DataFrame.div</a>(other[, axis, level, fill_value])</td>
        <td>Floating division of dataframe and other, element-wise (binary operator truediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.truediv.html#pandas.DataFrame.truediv" title="pandas.DataFrame.truediv">DataFrame.truediv</a>(other[, axis, level, …])</td>
        <td>Floating division of dataframe and other, element-wise (binary operator truediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.floordiv.html#pandas.DataFrame.floordiv" title="pandas.DataFrame.floordiv">DataFrame.floordiv</a>(other[, axis, level, …])</td>
        <td>Integer division of dataframe and other, element-wise (binary operator floordiv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.mod.html#pandas.DataFrame.mod" title="pandas.DataFrame.mod">DataFrame.mod</a>(other[, axis, level, fill_value])</td>
        <td>Modulo of dataframe and other, element-wise (binary operator mod).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pow.html#pandas.DataFrame.pow" title="pandas.DataFrame.pow">DataFrame.pow</a>(other[, axis, level, fill_value])</td>
        <td>Exponential power of dataframe and other, element-wise (binary operator pow).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dot.html#pandas.DataFrame.dot" title="pandas.DataFrame.dot">DataFrame.dot</a>(other)</td>
        <td>Compute the matrix mutiplication between the DataFrame and other.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.radd.html#pandas.DataFrame.radd" title="pandas.DataFrame.radd">DataFrame.radd</a>(other[, axis, level, fill_value])</td>
        <td>Addition of dataframe and other, element-wise (binary operator radd).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rsub.html#pandas.DataFrame.rsub" title="pandas.DataFrame.rsub">DataFrame.rsub</a>(other[, axis, level, fill_value])</td>
        <td>Subtraction of dataframe and other, element-wise (binary operator rsub).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rmul.html#pandas.DataFrame.rmul" title="pandas.DataFrame.rmul">DataFrame.rmul</a>(other[, axis, level, fill_value])</td>
        <td>Multiplication of dataframe and other, element-wise (binary operator rmul).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rdiv.html#pandas.DataFrame.rdiv" title="pandas.DataFrame.rdiv">DataFrame.rdiv</a>(other[, axis, level, fill_value])</td>
        <td>Floating division of dataframe and other, element-wise (binary operator rtruediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rtruediv.html#pandas.DataFrame.rtruediv" title="pandas.DataFrame.rtruediv">DataFrame.rtruediv</a>(other[, axis, level, …])</td>
        <td>Floating division of dataframe and other, element-wise (binary operator rtruediv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rfloordiv.html#pandas.DataFrame.rfloordiv" title="pandas.DataFrame.rfloordiv">DataFrame.rfloordiv</a>(other[, axis, level, …])</td>
        <td>Integer division of dataframe and other, element-wise (binary operator rfloordiv).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rmod.html#pandas.DataFrame.rmod" title="pandas.DataFrame.rmod">DataFrame.rmod</a>(other[, axis, level, fill_value])</td>
        <td>Modulo of dataframe and other, element-wise (binary operator rmod).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rpow.html#pandas.DataFrame.rpow" title="pandas.DataFrame.rpow">DataFrame.rpow</a>(other[, axis, level, fill_value])</td>
        <td>Exponential power of dataframe and other, element-wise (binary operator rpow).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.lt.html#pandas.DataFrame.lt" title="pandas.DataFrame.lt">DataFrame.lt</a>(other[, axis, level])</td>
        <td>Less than of dataframe and other, element-wise (binary operator lt).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.gt.html#pandas.DataFrame.gt" title="pandas.DataFrame.gt">DataFrame.gt</a>(other[, axis, level])</td>
        <td>Greater than of dataframe and other, element-wise (binary operator gt).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.le.html#pandas.DataFrame.le" title="pandas.DataFrame.le">DataFrame.le</a>(other[, axis, level])</td>
        <td>Less than or equal to of dataframe and other, element-wise (binary operator le).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ge.html#pandas.DataFrame.ge" title="pandas.DataFrame.ge">DataFrame.ge</a>(other[, axis, level])</td>
        <td>Greater than or equal to of dataframe and other, element-wise (binary operator ge).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ne.html#pandas.DataFrame.ne" title="pandas.DataFrame.ne">DataFrame.ne</a>(other[, axis, level])</td>
        <td>Not equal to of dataframe and other, element-wise (binary operator ne).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.eq.html#pandas.DataFrame.eq" title="pandas.DataFrame.eq">DataFrame.eq</a>(other[, axis, level])</td>
        <td>Equal to of dataframe and other, element-wise (binary operator eq).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.combine.html#pandas.DataFrame.combine" title="pandas.DataFrame.combine">DataFrame.combine</a>(other, func[, fill_value, …])</td>
        <td>Perform column-wise combine with another DataFrame based on a passed function.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.combine_first.html#pandas.DataFrame.combine_first" title="pandas.DataFrame.combine_first">DataFrame.combine_first</a>(other)</td>
        <td>Update null elements with value in the same location in other.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Function application, GroupBy &amp; Window</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html#pandas.DataFrame.apply" title="pandas.DataFrame.apply">DataFrame.apply</a>(func[, axis, broadcast, …])</td>
        <td>Apply a function along an axis of the DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.applymap.html#pandas.DataFrame.applymap" title="pandas.DataFrame.applymap">DataFrame.applymap</a>(func)</td>
        <td>Apply a function to a Dataframe elementwise.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pipe.html#pandas.DataFrame.pipe" title="pandas.DataFrame.pipe">DataFrame.pipe</a>(func, *args, **kwargs)</td>
        <td>Apply func(self, *args, **kwargs).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.agg.html#pandas.DataFrame.agg" title="pandas.DataFrame.agg">DataFrame.agg</a>(func[, axis])</td>
        <td>Aggregate using one or more operations over the specified axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.aggregate.html#pandas.DataFrame.aggregate" title="pandas.DataFrame.aggregate">DataFrame.aggregate</a>(func[, axis])</td>
        <td>Aggregate using one or more operations over the specified axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.transform.html#pandas.DataFrame.transform" title="pandas.DataFrame.transform">DataFrame.transform</a>(func[, axis])</td>
        <td>Call func on self producing a DataFrame with transformed values and that has the same axis length as self.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html#pandas.DataFrame.groupby" title="pandas.DataFrame.groupby">DataFrame.groupby</a>([by, axis, level, …])</td>
        <td>Group DataFrame or Series using a mapper or by a Series of columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rolling.html#pandas.DataFrame.rolling" title="pandas.DataFrame.rolling">DataFrame.rolling</a>(window[, min_periods, …])</td>
        <td>Provides rolling window calculations.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.expanding.html#pandas.DataFrame.expanding" title="pandas.DataFrame.expanding">DataFrame.expanding</a>([min_periods, center, axis])</td>
        <td>Provides expanding transformations.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ewm.html#pandas.DataFrame.ewm" title="pandas.DataFrame.ewm">DataFrame.ewm</a>([com, span, halflife, alpha, …])</td>
        <td>Provides exponential weighted functions.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Computations / Descriptive Stats</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.abs.html#pandas.DataFrame.abs" title="pandas.DataFrame.abs">DataFrame.abs</a>()</td>
        <td>Return a Series/DataFrame with absolute numeric value of each element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.all.html#pandas.DataFrame.all" title="pandas.DataFrame.all">DataFrame.all</a>([axis, bool_only, skipna, level])</td>
        <td>Return whether all elements are True, potentially over an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.any.html#pandas.DataFrame.any" title="pandas.DataFrame.any">DataFrame.any</a>([axis, bool_only, skipna, level])</td>
        <td>Return whether any element is True, potentially over an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.clip.html#pandas.DataFrame.clip" title="pandas.DataFrame.clip">DataFrame.clip</a>([lower, upper, axis, inplace])</td>
        <td>Trim values at input threshold(s).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.clip_lower.html#pandas.DataFrame.clip_lower" title="pandas.DataFrame.clip_lower">DataFrame.clip_lower</a>(threshold[, axis, inplace])</td>
        <td>(DEPRECATED) Trim values below a given threshold.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.clip_upper.html#pandas.DataFrame.clip_upper" title="pandas.DataFrame.clip_upper">DataFrame.clip_upper</a>(threshold[, axis, inplace])</td>
        <td>(DEPRECATED) Trim values above a given threshold.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.compound.html#pandas.DataFrame.compound" title="pandas.DataFrame.compound">DataFrame.compound</a>([axis, skipna, level])</td>
        <td>Return the compound percentage of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.corr.html#pandas.DataFrame.corr" title="pandas.DataFrame.corr">DataFrame.corr</a>([method, min_periods])</td>
        <td>Compute pairwise correlation of columns, excluding NA/null values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.corrwith.html#pandas.DataFrame.corrwith" title="pandas.DataFrame.corrwith">DataFrame.corrwith</a>(other[, axis, drop, method])</td>
        <td>Compute pairwise correlation between rows or columns of DataFrame with rows or columns of Series or DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.count.html#pandas.DataFrame.count" title="pandas.DataFrame.count">DataFrame.count</a>([axis, level, numeric_only])</td>
        <td>Count non-NA cells for each column or row.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cov.html#pandas.DataFrame.cov" title="pandas.DataFrame.cov">DataFrame.cov</a>([min_periods])</td>
        <td>Compute pairwise covariance of columns, excluding NA/null values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cummax.html#pandas.DataFrame.cummax" title="pandas.DataFrame.cummax">DataFrame.cummax</a>([axis, skipna])</td>
        <td>Return cumulative maximum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cummin.html#pandas.DataFrame.cummin" title="pandas.DataFrame.cummin">DataFrame.cummin</a>([axis, skipna])</td>
        <td>Return cumulative minimum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cumprod.html#pandas.DataFrame.cumprod" title="pandas.DataFrame.cumprod">DataFrame.cumprod</a>([axis, skipna])</td>
        <td>Return cumulative product over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cumsum.html#pandas.DataFrame.cumsum" title="pandas.DataFrame.cumsum">DataFrame.cumsum</a>([axis, skipna])</td>
        <td>Return cumulative sum over a DataFrame or Series axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.describe.html#pandas.DataFrame.describe" title="pandas.DataFrame.describe">DataFrame.describe</a>([percentiles, include, …])</td>
        <td>Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset&rsquo;s distribution, excluding NaN values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.diff.html#pandas.DataFrame.diff" title="pandas.DataFrame.diff">DataFrame.diff</a>([periods, axis])</td>
        <td>First discrete difference of element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.eval.html#pandas.DataFrame.eval" title="pandas.DataFrame.eval">DataFrame.eval</a>(expr[, inplace])</td>
        <td>Evaluate a string describing operations on DataFrame columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.kurt.html#pandas.DataFrame.kurt" title="pandas.DataFrame.kurt">DataFrame.kurt</a>([axis, skipna, level, …])</td>
        <td>Return unbiased kurtosis over requested axis using Fisher&rsquo;s definition of kurtosis (kurtosis of normal == 0.0).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.kurtosis.html#pandas.DataFrame.kurtosis" title="pandas.DataFrame.kurtosis">DataFrame.kurtosis</a>([axis, skipna, level, …])</td>
        <td>Return unbiased kurtosis over requested axis using Fisher&rsquo;s definition of kurtosis (kurtosis of normal == 0.0).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.mad.html#pandas.DataFrame.mad" title="pandas.DataFrame.mad">DataFrame.mad</a>([axis, skipna, level])</td>
        <td>Return the mean absolute deviation of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.max.html#pandas.DataFrame.max" title="pandas.DataFrame.max">DataFrame.max</a>([axis, skipna, level, …])</td>
        <td>Return the maximum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.mean.html#pandas.DataFrame.mean" title="pandas.DataFrame.mean">DataFrame.mean</a>([axis, skipna, level, …])</td>
        <td>Return the mean of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.median.html#pandas.DataFrame.median" title="pandas.DataFrame.median">DataFrame.median</a>([axis, skipna, level, …])</td>
        <td>Return the median of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.min.html#pandas.DataFrame.min" title="pandas.DataFrame.min">DataFrame.min</a>([axis, skipna, level, …])</td>
        <td>Return the minimum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.mode.html#pandas.DataFrame.mode" title="pandas.DataFrame.mode">DataFrame.mode</a>([axis, numeric_only, dropna])</td>
        <td>Get the mode(s) of each element along the selected axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pct_change.html#pandas.DataFrame.pct_change" title="pandas.DataFrame.pct_change">DataFrame.pct_change</a>([periods, fill_method, …])</td>
        <td>Percentage change between the current and a prior element.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.prod.html#pandas.DataFrame.prod" title="pandas.DataFrame.prod">DataFrame.prod</a>([axis, skipna, level, …])</td>
        <td>Return the product of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.product.html#pandas.DataFrame.product" title="pandas.DataFrame.product">DataFrame.product</a>([axis, skipna, level, …])</td>
        <td>Return the product of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.quantile.html#pandas.DataFrame.quantile" title="pandas.DataFrame.quantile">DataFrame.quantile</a>([q, axis, numeric_only, …])</td>
        <td>Return values at the given quantile over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rank.html#pandas.DataFrame.rank" title="pandas.DataFrame.rank">DataFrame.rank</a>([axis, method, numeric_only, …])</td>
        <td>Compute numerical data ranks (1 through n) along axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.round.html#pandas.DataFrame.round" title="pandas.DataFrame.round">DataFrame.round</a>([decimals])</td>
        <td>Round a DataFrame to a variable number of decimal places.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sem.html#pandas.DataFrame.sem" title="pandas.DataFrame.sem">DataFrame.sem</a>([axis, skipna, level, ddof, …])</td>
        <td>Return unbiased standard error of the mean over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.skew.html#pandas.DataFrame.skew" title="pandas.DataFrame.skew">DataFrame.skew</a>([axis, skipna, level, …])</td>
        <td>Return unbiased skew over requested axis Normalized by N-1.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sum.html#pandas.DataFrame.sum" title="pandas.DataFrame.sum">DataFrame.sum</a>([axis, skipna, level, …])</td>
        <td>Return the sum of the values for the requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.std.html#pandas.DataFrame.std" title="pandas.DataFrame.std">DataFrame.std</a>([axis, skipna, level, ddof, …])</td>
        <td>Return sample standard deviation over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.var.html#pandas.DataFrame.var" title="pandas.DataFrame.var">DataFrame.var</a>([axis, skipna, level, ddof, …])</td>
        <td>Return unbiased variance over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.nunique.html#pandas.DataFrame.nunique" title="pandas.DataFrame.nunique">DataFrame.nunique</a>([axis, dropna])</td>
        <td>Count distinct observations over requested axis.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Reindexing / Selection / Label manipulation</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.add_prefix.html#pandas.DataFrame.add_prefix" title="pandas.DataFrame.add_prefix">DataFrame.add_prefix</a>(prefix)</td>
        <td>Prefix labels with string prefix.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.add_suffix.html#pandas.DataFrame.add_suffix" title="pandas.DataFrame.add_suffix">DataFrame.add_suffix</a>(suffix)</td>
        <td>Suffix labels with string suffix.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.align.html#pandas.DataFrame.align" title="pandas.DataFrame.align">DataFrame.align</a>(other[, join, axis, level, …])</td>
        <td>Align two objects on their axes with the specified join method for each axis Index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.at_time.html#pandas.DataFrame.at_time" title="pandas.DataFrame.at_time">DataFrame.at_time</a>(time[, asof, axis])</td>
        <td>Select values at particular time of day (e.g.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.between_time.html#pandas.DataFrame.between_time" title="pandas.DataFrame.between_time">DataFrame.between_time</a>(start_time, end_time)</td>
        <td>Select values between particular times of the day (e.g., 9:00-9:30 AM).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html#pandas.DataFrame.drop" title="pandas.DataFrame.drop">DataFrame.drop</a>([labels, axis, index, …])</td>
        <td>Drop specified labels from rows or columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop_duplicates.html#pandas.DataFrame.drop_duplicates" title="pandas.DataFrame.drop_duplicates">DataFrame.drop_duplicates</a>([subset, keep, …])</td>
        <td>Return DataFrame with duplicate rows removed, optionally only considering certain columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.duplicated.html#pandas.DataFrame.duplicated" title="pandas.DataFrame.duplicated">DataFrame.duplicated</a>([subset, keep])</td>
        <td>Return boolean Series denoting duplicate rows, optionally only considering certain columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.equals.html#pandas.DataFrame.equals" title="pandas.DataFrame.equals">DataFrame.equals</a>(other)</td>
        <td>Test whether two objects contain the same elements.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.filter.html#pandas.DataFrame.filter" title="pandas.DataFrame.filter">DataFrame.filter</a>([items, like, regex, axis])</td>
        <td>Subset rows or columns of dataframe according to labels in the specified index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.first.html#pandas.DataFrame.first" title="pandas.DataFrame.first">DataFrame.first</a>(offset)</td>
        <td>Convenience method for subsetting initial periods of time series data based on a date offset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.head.html#pandas.DataFrame.head" title="pandas.DataFrame.head">DataFrame.head</a>([n])</td>
        <td>Return the first n rows.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.idxmax.html#pandas.DataFrame.idxmax" title="pandas.DataFrame.idxmax">DataFrame.idxmax</a>([axis, skipna])</td>
        <td>Return index of first occurrence of maximum over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.idxmin.html#pandas.DataFrame.idxmin" title="pandas.DataFrame.idxmin">DataFrame.idxmin</a>([axis, skipna])</td>
        <td>Return index of first occurrence of minimum over requested axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.last.html#pandas.DataFrame.last" title="pandas.DataFrame.last">DataFrame.last</a>(offset)</td>
        <td>Convenience method for subsetting final periods of time series data based on a date offset.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reindex.html#pandas.DataFrame.reindex" title="pandas.DataFrame.reindex">DataFrame.reindex</a>([labels, index, columns, …])</td>
        <td>Conform DataFrame to new index with optional filling logic, placing NA/NaN in locations having no value in the previous index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reindex_axis.html#pandas.DataFrame.reindex_axis" title="pandas.DataFrame.reindex_axis">DataFrame.reindex_axis</a>(labels[, axis, …])</td>
        <td>(DEPRECATED) Conform input object to new index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reindex_like.html#pandas.DataFrame.reindex_like" title="pandas.DataFrame.reindex_like">DataFrame.reindex_like</a>(other[, method, …])</td>
        <td>Return an object with matching indices as other object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename.html#pandas.DataFrame.rename" title="pandas.DataFrame.rename">DataFrame.rename</a>([mapper, index, columns, …])</td>
        <td>Alter axes labels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.rename_axis.html#pandas.DataFrame.rename_axis" title="pandas.DataFrame.rename_axis">DataFrame.rename_axis</a>([mapper, index, …])</td>
        <td>Set the name of the axis for the index or columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html#pandas.DataFrame.reset_index" title="pandas.DataFrame.reset_index">DataFrame.reset_index</a>([level, drop, …])</td>
        <td>Reset the index, or a level of it.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sample.html#pandas.DataFrame.sample" title="pandas.DataFrame.sample">DataFrame.sample</a>([n, frac, replace, …])</td>
        <td>Return a random sample of items from an axis of object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.select.html#pandas.DataFrame.select" title="pandas.DataFrame.select">DataFrame.select</a>(crit[, axis])</td>
        <td>(DEPRECATED) Return data corresponding to axis labels matching criteria.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_axis.html#pandas.DataFrame.set_axis" title="pandas.DataFrame.set_axis">DataFrame.set_axis</a>(labels[, axis, inplace])</td>
        <td>Assign desired index to given axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_index.html#pandas.DataFrame.set_index" title="pandas.DataFrame.set_index">DataFrame.set_index</a>(keys[, drop, append, …])</td>
        <td>Set the DataFrame index using existing columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tail.html#pandas.DataFrame.tail" title="pandas.DataFrame.tail">DataFrame.tail</a>([n])</td>
        <td>Return the last n rows.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.take.html#pandas.DataFrame.take" title="pandas.DataFrame.take">DataFrame.take</a>(indices[, axis, convert, is_copy])</td>
        <td>Return the elements in the given <em>positional</em> indices along an axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.truncate.html#pandas.DataFrame.truncate" title="pandas.DataFrame.truncate">DataFrame.truncate</a>([before, after, axis, copy])</td>
        <td>Truncate a Series or DataFrame before and after some index value.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Missing data handling</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html#pandas.DataFrame.dropna" title="pandas.DataFrame.dropna">DataFrame.dropna</a>([axis, how, thresh, …])</td>
        <td>Remove missing values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html#pandas.DataFrame.fillna" title="pandas.DataFrame.fillna">DataFrame.fillna</a>([value, method, axis, …])</td>
        <td>Fill NA/NaN values using the specified method.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.replace.html#pandas.DataFrame.replace" title="pandas.DataFrame.replace">DataFrame.replace</a>([to_replace, value, …])</td>
        <td>Replace values given in to_replace with value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.interpolate.html#pandas.DataFrame.interpolate" title="pandas.DataFrame.interpolate">DataFrame.interpolate</a>([method, axis, limit, …])</td>
        <td>Interpolate values according to different methods.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Reshaping, sorting, transposing</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.droplevel.html#pandas.DataFrame.droplevel" title="pandas.DataFrame.droplevel">DataFrame.droplevel</a>(level[, axis])</td>
        <td>Return DataFrame with requested index / column level(s) removed.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pivot.html#pandas.DataFrame.pivot" title="pandas.DataFrame.pivot">DataFrame.pivot</a>([index, columns, values])</td>
        <td>Return reshaped DataFrame organized by given index / column values.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.pivot_table.html#pandas.DataFrame.pivot_table" title="pandas.DataFrame.pivot_table">DataFrame.pivot_table</a>([values, index, …])</td>
        <td>Create a spreadsheet-style pivot table as a DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reorder_levels.html#pandas.DataFrame.reorder_levels" title="pandas.DataFrame.reorder_levels">DataFrame.reorder_levels</a>(order[, axis])</td>
        <td>Rearrange index levels using input order.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html#pandas.DataFrame.sort_values" title="pandas.DataFrame.sort_values">DataFrame.sort_values</a>(by[, axis, ascending, …])</td>
        <td>Sort by the values along either axis</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_index.html#pandas.DataFrame.sort_index" title="pandas.DataFrame.sort_index">DataFrame.sort_index</a>([axis, level, …])</td>
        <td>Sort object by labels (along an axis)</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.nlargest.html#pandas.DataFrame.nlargest" title="pandas.DataFrame.nlargest">DataFrame.nlargest</a>(n, columns[, keep])</td>
        <td>Return the first n rows ordered by columns in descending order.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.nsmallest.html#pandas.DataFrame.nsmallest" title="pandas.DataFrame.nsmallest">DataFrame.nsmallest</a>(n, columns[, keep])</td>
        <td>Return the first n rows ordered by columns in ascending order.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.swaplevel.html#pandas.DataFrame.swaplevel" title="pandas.DataFrame.swaplevel">DataFrame.swaplevel</a>([i, j, axis])</td>
        <td>Swap levels i and j in a MultiIndex on a particular axis.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.stack.html#pandas.DataFrame.stack" title="pandas.DataFrame.stack">DataFrame.stack</a>([level, dropna])</td>
        <td>Stack the prescribed level(s) from columns to index.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.unstack.html#pandas.DataFrame.unstack" title="pandas.DataFrame.unstack">DataFrame.unstack</a>([level, fill_value])</td>
        <td>Pivot a level of the (necessarily hierarchical) index labels, returning a DataFrame having a new level of column labels whose inner-most level consists of the pivoted index labels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.swapaxes.html#pandas.DataFrame.swapaxes" title="pandas.DataFrame.swapaxes">DataFrame.swapaxes</a>(axis1, axis2[, copy])</td>
        <td>Interchange axes and swap values axes appropriately.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.melt.html#pandas.DataFrame.melt" title="pandas.DataFrame.melt">DataFrame.melt</a>([id_vars, value_vars, …])</td>
        <td>Unpivots a DataFrame from wide format to long format, optionally leaving identifier variables set.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.squeeze.html#pandas.DataFrame.squeeze" title="pandas.DataFrame.squeeze">DataFrame.squeeze</a>([axis])</td>
        <td>Squeeze 1 dimensional axis objects into scalars.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_panel.html#pandas.DataFrame.to_panel" title="pandas.DataFrame.to_panel">DataFrame.to_panel</a>()</td>
        <td>(DEPRECATED) Transform long (stacked) format (DataFrame) into wide (3D, Panel) format.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_xarray.html#pandas.DataFrame.to_xarray" title="pandas.DataFrame.to_xarray">DataFrame.to_xarray</a>()</td>
        <td>Return an xarray object from the pandas object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.T.html#pandas.DataFrame.T" title="pandas.DataFrame.T">DataFrame.T</a></td>
        <td>Transpose index and columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.transpose.html#pandas.DataFrame.transpose" title="pandas.DataFrame.transpose">DataFrame.transpose</a>(*args, **kwargs)</td>
        <td>Transpose index and columns.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Combining / joining / merging</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.append.html#pandas.DataFrame.append" title="pandas.DataFrame.append">DataFrame.append</a>(other[, ignore_index, …])</td>
        <td>Append rows of other to the end of caller, returning a new object.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.assign.html#pandas.DataFrame.assign" title="pandas.DataFrame.assign">DataFrame.assign</a>(**kwargs)</td>
        <td>Assign new columns to a DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html#pandas.DataFrame.join" title="pandas.DataFrame.join">DataFrame.join</a>(other[, on, how, lsuffix, …])</td>
        <td>Join columns of another DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html#pandas.DataFrame.merge" title="pandas.DataFrame.merge">DataFrame.merge</a>(right[, how, on, left_on, …])</td>
        <td>Merge DataFrame or named Series objects with a database-style join.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.update.html#pandas.DataFrame.update" title="pandas.DataFrame.update">DataFrame.update</a>(other[, join, overwrite, …])</td>
        <td>Modify in place using non-NA values from another DataFrame.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Time series-related</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.asfreq.html#pandas.DataFrame.asfreq" title="pandas.DataFrame.asfreq">DataFrame.asfreq</a>(freq[, method, how, …])</td>
        <td>Convert TimeSeries to specified frequency.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.asof.html#pandas.DataFrame.asof" title="pandas.DataFrame.asof">DataFrame.asof</a>(where[, subset])</td>
        <td>Return the last row(s) without any NaNs before where.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.shift.html#pandas.DataFrame.shift" title="pandas.DataFrame.shift">DataFrame.shift</a>([periods, freq, axis, …])</td>
        <td>Shift index by desired number of periods with an optional time freq.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.slice_shift.html#pandas.DataFrame.slice_shift" title="pandas.DataFrame.slice_shift">DataFrame.slice_shift</a>([periods, axis])</td>
        <td>Equivalent to shift without copying data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tshift.html#pandas.DataFrame.tshift" title="pandas.DataFrame.tshift">DataFrame.tshift</a>([periods, freq, axis])</td>
        <td>Shift the time index, using the index&rsquo;s frequency if available.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.first_valid_index.html#pandas.DataFrame.first_valid_index" title="pandas.DataFrame.first_valid_index">DataFrame.first_valid_index</a>()</td>
        <td>Return index for first non-NA/null value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.last_valid_index.html#pandas.DataFrame.last_valid_index" title="pandas.DataFrame.last_valid_index">DataFrame.last_valid_index</a>()</td>
        <td>Return index for last non-NA/null value.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.resample.html#pandas.DataFrame.resample" title="pandas.DataFrame.resample">DataFrame.resample</a>(rule[, how, axis, …])</td>
        <td>Resample time-series data.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_period.html#pandas.DataFrame.to_period" title="pandas.DataFrame.to_period">DataFrame.to_period</a>([freq, axis, copy])</td>
        <td>Convert DataFrame from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_timestamp.html#pandas.DataFrame.to_timestamp" title="pandas.DataFrame.to_timestamp">DataFrame.to_timestamp</a>([freq, how, axis, copy])</td>
        <td>Cast to DatetimeIndex of timestamps, at <em>beginning</em> of period.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tz_convert.html#pandas.DataFrame.tz_convert" title="pandas.DataFrame.tz_convert">DataFrame.tz_convert</a>(tz[, axis, level, copy])</td>
        <td>Convert tz-aware axis to target time zone.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tz_localize.html#pandas.DataFrame.tz_localize" title="pandas.DataFrame.tz_localize">DataFrame.tz_localize</a>(tz[, axis, level, …])</td>
        <td>Localize tz-naive index of a Series or DataFrame to target time zone.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Plotting</h2>
  <p>DataFrame.plot is both a callable method and a namespace attribute for specific plotting methods of the form DataFrame.plot.&lt;kind&gt;.</p>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html#pandas.DataFrame.plot" title="pandas.DataFrame.plot">DataFrame.plot</a>([x, y, kind, ax, ….])</td>
        <td>DataFrame plotting accessor and method</td>
      </tr>
    </tbody>
  </table>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.area.html#pandas.DataFrame.plot.area" title="pandas.DataFrame.plot.area">DataFrame.plot.area</a>([x, y])</td>
        <td>Draw a stacked area plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.bar.html#pandas.DataFrame.plot.bar" title="pandas.DataFrame.plot.bar">DataFrame.plot.bar</a>([x, y])</td>
        <td>Vertical bar plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.barh.html#pandas.DataFrame.plot.barh" title="pandas.DataFrame.plot.barh">DataFrame.plot.barh</a>([x, y])</td>
        <td>Make a horizontal bar plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.box.html#pandas.DataFrame.plot.box" title="pandas.DataFrame.plot.box">DataFrame.plot.box</a>([by])</td>
        <td>Make a box plot of the DataFrame columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.density.html#pandas.DataFrame.plot.density" title="pandas.DataFrame.plot.density">DataFrame.plot.density</a>([bw_method, ind])</td>
        <td>Generate Kernel Density Estimate plot using Gaussian kernels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.hexbin.html#pandas.DataFrame.plot.hexbin" title="pandas.DataFrame.plot.hexbin">DataFrame.plot.hexbin</a>(x, y[, C, …])</td>
        <td>Generate a hexagonal binning plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.hist.html#pandas.DataFrame.plot.hist" title="pandas.DataFrame.plot.hist">DataFrame.plot.hist</a>([by, bins])</td>
        <td>Draw one histogram of the DataFrame&rsquo;s columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.kde.html#pandas.DataFrame.plot.kde" title="pandas.DataFrame.plot.kde">DataFrame.plot.kde</a>([bw_method, ind])</td>
        <td>Generate Kernel Density Estimate plot using Gaussian kernels.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.line.html#pandas.DataFrame.plot.line" title="pandas.DataFrame.plot.line">DataFrame.plot.line</a>([x, y])</td>
        <td>Plot DataFrame columns as lines.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.pie.html#pandas.DataFrame.plot.pie" title="pandas.DataFrame.plot.pie">DataFrame.plot.pie</a>([y])</td>
        <td>Generate a pie plot.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.scatter.html#pandas.DataFrame.plot.scatter" title="pandas.DataFrame.plot.scatter">DataFrame.plot.scatter</a>(x, y[, s, c])</td>
        <td>Create a scatter plot with varying marker point size and color.</td>
      </tr>
    </tbody>
  </table>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.boxplot.html#pandas.DataFrame.boxplot" title="pandas.DataFrame.boxplot">DataFrame.boxplot</a>([column, by, ax, …])</td>
        <td>Make a box plot from DataFrame columns.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.hist.html#pandas.DataFrame.hist" title="pandas.DataFrame.hist">DataFrame.hist</a>([column, by, grid, …])</td>
        <td>Make a histogram of the DataFrame&rsquo;s.</td>
      </tr>
    </tbody>
  </table>
</div>
<div class="w3-container">
  <h2>Serialization / IO / Conversion</h2>
  <table class="w3-table-all w3-hoverable">
    <colgroup>
    <col width="10%">
    <col width="90%">
    </colgroup>
    <tbody valign="top">
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.from_csv.html#pandas.DataFrame.from_csv" title="pandas.DataFrame.from_csv">DataFrame.from_csv</a>(path[, header, sep, …])</td>
        <td>(DEPRECATED) Read CSV file.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.from_dict.html#pandas.DataFrame.from_dict" title="pandas.DataFrame.from_dict">DataFrame.from_dict</a>(data[, orient, dtype, …])</td>
        <td>Construct DataFrame from dict of array-like or dicts.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.from_items.html#pandas.DataFrame.from_items" title="pandas.DataFrame.from_items">DataFrame.from_items</a>(items[, columns, orient])</td>
        <td>(DEPRECATED) Construct a DataFrame from a list of tuples.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.from_records.html#pandas.DataFrame.from_records" title="pandas.DataFrame.from_records">DataFrame.from_records</a>(data[, index, …])</td>
        <td>Convert structured or record ndarray to DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.info.html#pandas.DataFrame.info" title="pandas.DataFrame.info">DataFrame.info</a>([verbose, buf, max_cols, …])</td>
        <td>Print a concise summary of a DataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_parquet.html#pandas.DataFrame.to_parquet" title="pandas.DataFrame.to_parquet">DataFrame.to_parquet</a>(fname[, engine, …])</td>
        <td>Write a DataFrame to the binary parquet format.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_pickle.html#pandas.DataFrame.to_pickle" title="pandas.DataFrame.to_pickle">DataFrame.to_pickle</a>(path[, compression, …])</td>
        <td>Pickle (serialize) object to file.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html#pandas.DataFrame.to_csv" title="pandas.DataFrame.to_csv">DataFrame.to_csv</a>([path_or_buf, sep, na_rep, …])</td>
        <td>Write object to a comma-separated values (csv) file.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_hdf.html#pandas.DataFrame.to_hdf" title="pandas.DataFrame.to_hdf">DataFrame.to_hdf</a>(path_or_buf, key, **kwargs)</td>
        <td>Write the contained data to an HDF5 file using HDFStore.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_sql.html#pandas.DataFrame.to_sql" title="pandas.DataFrame.to_sql">DataFrame.to_sql</a>(name, con[, schema, …])</td>
        <td>Write records stored in a DataFrame to a SQL database.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_dict.html#pandas.DataFrame.to_dict" title="pandas.DataFrame.to_dict">DataFrame.to_dict</a>([orient, into])</td>
        <td>Convert the DataFrame to a dictionary.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_excel.html#pandas.DataFrame.to_excel" title="pandas.DataFrame.to_excel">DataFrame.to_excel</a>(excel_writer[, …])</td>
        <td>Write object to an Excel sheet.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_json.html#pandas.DataFrame.to_json" title="pandas.DataFrame.to_json">DataFrame.to_json</a>([path_or_buf, orient, …])</td>
        <td>Convert the object to a JSON string.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_html.html#pandas.DataFrame.to_html" title="pandas.DataFrame.to_html">DataFrame.to_html</a>([buf, columns, col_space, …])</td>
        <td>Render a DataFrame as an HTML table.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_feather.html#pandas.DataFrame.to_feather" title="pandas.DataFrame.to_feather">DataFrame.to_feather</a>(fname)</td>
        <td>Write out the binary feather-format for DataFrames.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_latex.html#pandas.DataFrame.to_latex" title="pandas.DataFrame.to_latex">DataFrame.to_latex</a>([buf, columns, …])</td>
        <td>Render an object to a LaTeX tabular environment table.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_stata.html#pandas.DataFrame.to_stata" title="pandas.DataFrame.to_stata">DataFrame.to_stata</a>(fname[, convert_dates, …])</td>
        <td>Export DataFrame object to Stata dta format.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_msgpack.html#pandas.DataFrame.to_msgpack" title="pandas.DataFrame.to_msgpack">DataFrame.to_msgpack</a>([path_or_buf, encoding])</td>
        <td>Serialize object to input file path using msgpack format.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_gbq.html#pandas.DataFrame.to_gbq" title="pandas.DataFrame.to_gbq">DataFrame.to_gbq</a>(destination_table[, …])</td>
        <td>Write a DataFrame to a Google BigQuery table.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_records.html#pandas.DataFrame.to_records" title="pandas.DataFrame.to_records">DataFrame.to_records</a>([index, …])</td>
        <td>Convert DataFrame to a NumPy record array.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_sparse.html#pandas.DataFrame.to_sparse" title="pandas.DataFrame.to_sparse">DataFrame.to_sparse</a>([fill_value, kind])</td>
        <td>Convert to SparseDataFrame.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_dense.html#pandas.DataFrame.to_dense" title="pandas.DataFrame.to_dense">DataFrame.to_dense</a>()</td>
        <td>Return dense representation of NDFrame (as opposed to sparse).</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_string.html#pandas.DataFrame.to_string" title="pandas.DataFrame.to_string">DataFrame.to_string</a>([buf, columns, …])</td>
        <td>Render a DataFrame to a console-friendly tabular output.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_clipboard.html#pandas.DataFrame.to_clipboard" title="pandas.DataFrame.to_clipboard">DataFrame.to_clipboard</a>([excel, sep])</td>
        <td>Copy object to the system clipboard.</td>
      </tr>
      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.style.html#pandas.DataFrame.style" title="pandas.DataFrame.style">DataFrame.style</a></td>
        <td>Property returning a Styler object containing methods for building a styled HTML representation fo the DataFrame.</td>
      </tr>
    </tbody>
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  <h2>Sparse</h2>
  <table class="w3-table-all w3-hoverable">
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    <col width="90%">
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      <tr>
        <td><a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.SparseDataFrame.to_coo.html#pandas.SparseDataFrame.to_coo" title="pandas.SparseDataFrame.to_coo">SparseDataFrame.to_coo</a>()</td>
        <td>Return the contents of the frame as a sparse SciPy COO matrix.</td>
      </tr>
    </tbody>
  </table>
</div>

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